Wind power plant control method and device, equipment and storage medium
By dividing the wind farm into shared turbine clusters and using other wind turbines to correct wind direction deviations, the problem of unreliable wind speed and direction detection for wind turbines has been solved, thus improving the safety of wind turbines.
Patent Information
- Application Number
- CN202511735266.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-03-17
AI Technical Summary
Meteorological instruments on wind turbines are susceptible to weather and other environmental factors, leading to unreliable wind speed and direction readings, uneven loads on the wind turbines, and reduced safety.
By dividing the wind turbines within the wind farm into shared turbine clusters, wind direction deviations can be corrected using other wind turbines, the current wind direction of the target wind turbine can be determined, and accurate wind speed and direction can be transmitted to adjust the operating status.
This improves the reliability of wind direction and speed detection for wind turbines, reduces unbalanced loads, and enhances the safety of wind turbines.
Smart Images
Figure CN121676244A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wind power generation technology, and in particular to a control method, device, equipment, and storage medium for a wind farm. Background Technology
[0002] During the operation of a wind turbine, in order to ensure the structural safety of the wind turbine, it is necessary to adjust the operating status of the wind turbine according to the wind speed and wind direction.
[0003] In related technologies, the wind speed and direction during the operation of wind turbines are mainly detected by meteorological instruments installed on the top of the wind turbine nacelle.
[0004] However, due to environmental factors such as weather, the meteorological instruments on the top of the nacelle are prone to malfunction. When the meteorological instruments malfunction, the wind speed and direction provided are unreliable. Based on unreliable wind speed and direction, the wind turbine cannot accurately yaw, resulting in the wind turbine bearing unbalanced loads and easily causing structural damage, thereby reducing the safety of the wind turbine. Summary of the Invention
[0005] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.
[0006] This application provides a wind farm control method, device, equipment, and storage medium that enables wind turbines to operate based on more accurate wind speed and direction, thereby reducing the possibility of structural risks and improving the safety of wind turbines.
[0007] In a first aspect, embodiments of this application provide a wind farm control method applied to a server, the method comprising: The wind turbines within the wind farm are divided into multiple shared turbine clusters; From multiple shared turbine clusters, determine the target shared turbine cluster to which the target wind turbine belongs; the target wind turbine is any wind turbine in the wind farm. Based on the current wind speed of each wind turbine in the target shared turbine cluster, determine the wind direction deviation of each wind turbine. Based on the wind direction deviation of each wind turbine in the target shared turbine cluster, the wind direction of each wind turbine is corrected separately. Based on the corrected wind direction of each wind turbine in the target shared turbine cluster, determine the current wind direction of the target wind turbine; The current wind direction and current wind speed of the target wind turbine are transmitted to the target wind turbine so that the target wind turbine can adjust its operating status according to the current wind direction and current wind speed.
[0008] Optionally, the wind turbines within the wind farm are divided into multiple shared turbine clusters, including: grouping them based on historical wind condition data of each wind turbine in the wind farm to obtain multiple wind turbine groups; filtering out wind turbines affected by wake interference from multiple wind turbine groups; determining the turbulence intensity of each wind turbine based on historical wind condition data of each wind turbine in the wind farm; assigning wind turbines with the same turbulence level in each wind turbine group to the same shared turbine cluster according to the turbulence intensity of each wind turbine in the wind farm to obtain multiple shared turbine clusters; and assigning wind turbines within a preset distance in each shared turbine cluster to the same shared turbine group to obtain multiple shared turbine groups.
[0009] Optionally, before grouping based on the historical wind condition data of each wind turbine in the wind farm, the method further includes: performing preprocessing on the historical wind condition data of each wind turbine; wherein the preprocessing includes at least time synchronization processing, outlier data removal processing, and filtering processing.
[0010] Optionally, based on the current wind speed of each wind turbine in the target shared turbine cluster, the wind direction deviation of each wind turbine is determined, including: for each wind turbine in the target shared turbine cluster, the current wind speed of the wind turbine is input into the deviation calculation model so that the deviation calculation model can identify the current wind speed of the wind turbine and output the wind direction deviation of the wind turbine.
[0011] Optionally, before inputting the wind speed of the wind turbine into the deviation calculation model, the method may further include: obtaining the historical wind speed of the wind turbine; dividing the historical wind speed into multiple wind speed intervals; determining the wind direction deviation of each wind speed interval to obtain the correlation between each wind speed interval and the wind direction deviation; and training the initial model so that the initial model learns the correlation between each wind speed interval and the wind direction deviation to obtain a trained deviation calculation model.
[0012] Optionally, the current wind direction and current wind speed of the target wind turbine are transmitted to the target wind turbine, including: determining whether the communication of the target wind turbine is normal based on the heartbeat information sent by the target wind turbine; transmitting the current wind direction and current wind speed to the target wind turbine when the communication of the target wind turbine is normal; and sending a communication error message when the communication of the target wind turbine is abnormal.
[0013] Secondly, embodiments of this application provide a wind farm control device integrated into a server, the device comprising: The wind farm partitioning module is configured to partition the wind turbines within the wind farm, resulting in multiple shared turbine clusters; The target determination module is configured to determine the target shared turbine group to which the target wind turbine belongs from multiple shared turbine groups; the target wind turbine is any wind turbine in the wind farm. The deviation determination module is configured to determine the wind direction deviation of each wind turbine based on the current wind speed of each wind turbine in the target shared turbine cluster. The wind direction correction module is configured to correct the wind direction of each wind turbine based on the wind direction deviation of each wind turbine in the target shared turbine cluster. The wind direction determination module is configured to determine the current wind direction of the target wind turbine based on the corrected wind direction of each wind turbine in the target shared turbine cluster. The wind condition transmission module is configured to transmit the current wind direction and current wind speed of the target wind turbine to the target wind turbine so that the target wind turbine can adjust its operating status according to the current wind direction and current wind speed.
[0014] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing program instructions, wherein the processor is configured to execute the wind farm control method of the first aspect when running the program instructions.
[0015] Fourthly, embodiments of this application provide a storage medium storing program instructions, wherein the program instructions, when running, execute the wind farm control method of the first aspect.
[0016] The wind farm control method, apparatus, equipment, and storage medium provided in the embodiments of this application can achieve the following technical effects: For wind turbines deployed within a wind farm, the server divides them into multiple shared turbine clusters. Within the same shared turbine cluster, the wind speeds and directions of the wind turbines are relatively similar. For any target wind turbine within the wind farm, the target shared turbine cluster to which it belongs can be determined. For each wind turbine in the target shared turbine cluster, the wind direction deviation of the turbine at the current wind speed can be determined, and the wind direction can be corrected based on the deviation. After the wind direction of each wind turbine in the target shared turbine cluster is corrected, the current wind direction of the target wind turbine can be determined based on the corrected wind direction of each turbine. The current wind speed and current wind direction of the target wind turbine are then transmitted to the target wind turbine so that it can adjust its operating status accordingly.
[0017] In this embodiment, the current wind direction of the target wind turbine is determined based on the wind direction after correction for deviations from each wind turbine in the target shared turbine cluster. This means that wind direction deviations are considered when determining the current wind direction of the target wind turbine, resulting in a more accurate current wind direction. Due to the high consistency among wind turbines within the target shared turbine cluster, even if the wind speed and direction detected by the target wind turbine's own meteorological instruments are unreliable, the current wind direction of the target wind turbine can still be determined using the corrected wind directions from other wind turbines in the target shared turbine cluster, ensuring the reliability of the target wind turbine's current wind direction. Operating the wind turbine based on more accurate and reliable wind direction and speed reduces the likelihood of unbalanced loads on the wind turbine, thereby lowering the possibility of structural damage and improving the safety of the wind turbine.
[0018] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description
[0019] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are considered similar elements. The drawings do not constitute a limitation of scale, and wherein: Figure 1 This is a schematic diagram of a wind turbine provided in an embodiment of this application; Figure 2 This is a flowchart of a wind farm control method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating the division of shared turbine clusters within a wind farm, as provided in an embodiment of this application. Figure 4 This is a flowchart of a training bias calculation model provided in an embodiment of this application; Figure 5 This is a schematic diagram of a wind farm control device provided in an embodiment of this application; Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation
[0020] A wind turbine is a device that converts wind energy into electrical energy. It captures the kinetic energy of the wind through its blades, converts the kinetic energy into the mechanical energy of the turbine shaft, and then the generator converts the mechanical energy into electrical energy. During the operation of a wind turbine, in order to ensure the structural safety of the wind turbine, it is necessary to adjust the operating status of the wind turbine according to the wind speed and direction, such as adjusting the yaw and pitch settings.
[0021] In related technologies, meteorological instruments (such as anemometers) installed on the top of the wind turbine nacelle are mainly used to detect the wind speed and direction during the operation of the wind turbine, so that the wind turbine can adjust its operating status according to the detected wind speed and direction.
[0022] However, wind turbines are typically located outdoors, and the meteorological instruments mounted on the nacelle are susceptible to malfunction due to weather and other environmental factors, especially in severe weather. When meteorological instruments malfunction, the wind speed and direction information provided becomes unreliable. This unreliable information prevents the wind turbine from accurately yawing, leading to uneven loads and structural damage, thus reducing its safety. For example, unreliable wind speed and direction information may arise from a malfunctioning meteorological instrument that fails to update the information in a timely manner, thus failing to accurately reflect current wind conditions, or from providing abrupt and abnormally fluctuating data that is meaningless.
[0023] Therefore, embodiments of this application provide a control method, apparatus, equipment, and storage medium for a wind farm. In this scheme, the current wind direction of the target wind turbine can be determined based on the wind direction of each wind turbine in the target shared turbine group to which the target wind turbine belongs, after correction for deviations. Since wind direction deviations are already considered when determining the wind direction of the target wind turbine, the current wind direction of the target wind turbine will be relatively accurate. Combined with the high consistency among wind turbines within the target shared turbine group, the current wind direction of the target wind turbine can be determined by using the wind directions of other wind turbines in the target shared turbine group after correction for deviations, ensuring the reliability of the current wind direction of the target wind turbine. Wind turbines operating based on more accurate and reliable wind direction and speed can reduce the occurrence of unbalanced loads on the wind turbines, thereby reducing the possibility of structural risks and improving the safety of the wind turbines.
[0024] To provide a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this application. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.
[0025] The terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. Unless otherwise stated, the term "a plurality of" means two or more, and the term "multiple units" means two or more.
[0026] In this embodiment, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B. The term "and / or" describes an association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B. The term "correspondence" can refer to an association or binding relationship; A corresponding to B means that there is an association or binding relationship between A and B.
[0027] Combination Figure 1 As shown in the figure, this application embodiment provides a wind turbine deployed in a wind farm, and the wind turbine establishes a connection with server 10. Wherein: Server 10 is used to acquire and store data from wind turbines (such as environmental data, operational data, etc.) and operates based on the wind turbine's data controller. Server 10 can run an interactive interface, through which maintenance personnel can understand the operating status of wind turbines in the wind farm and input control operations to control the operation of wind turbines in the wind farm. For example, the server can be a SCADA (Supervisory Control And Data Acquisition) server, or other electronic devices that implement control functions.
[0028] The wind turbine includes blades 11, a hub 12, a nacelle 13, a tower 14, and a foundation 15. The blades 11 are mounted on the hub 12 to capture the kinetic energy of the wind. The number of blades 11 can be customized according to requirements; this embodiment does not limit this. The hub 12 is connected to a generator located inside the nacelle 13. The hub 12 converts the kinetic energy of the wind into mechanical energy, and the generator converts the mechanical energy into electrical energy. The nacelle 13 is equipped with a yaw device and a pitch device. The yaw device adjusts the yaw angle of the nacelle 13 according to wind conditions, i.e., controls the rotation of the nacelle 13. The pitch device adjusts the angle between the blades 11 and the wind direction, thus ensuring both the power generation efficiency and the structural safety of the wind turbine. The tower 14 supports the blades 11, hub 12, and nacelle 13. The foundation 15 is used to install or fix the tower 14 to the ground, thereby supporting the entire wind turbine.
[0029] It is understandable that, such as Figure 1 The illustration shows only one wind turbine, but in a real wind farm, multiple wind turbines will be deployed.
[0030] Optionally, a meteorological instrument 131 is installed on the top of the nacelle 13. The meteorological instrument 131 is used to detect wind condition data such as wind speed and wind direction of the wind turbine. For example, the meteorological instrument 131 can be a wind speed and direction sensor or a wind speed and direction instrument.
[0031] The following describes the method embodiments provided in this application.
[0032] Combination Figure 2 As shown in the figure, this application provides a wind farm control method, which can be applied to the aforementioned server. The method specifically includes the following steps: S21 divides the wind turbines within the wind farm into multiple shared turbine clusters.
[0033] In this step, considering that multiple wind turbines are typically deployed over a large area of a wind farm, the multiple wind turbines within the wind farm are divided into several shared turbine clusters. A shared turbine cluster consists of multiple wind turbines centrally deployed within the wind farm, with wind directions and speeds being relatively similar among the turbines within the same shared turbine cluster. The purpose of dividing into shared turbine clusters is to concentrate wind turbines with high consistency, allowing multiple wind turbines to share operational data and environmental conditions. This consistency is mainly reflected in similar wind conditions, similar geographical locations, and similar environmental parameters.
[0034] S22, determine the target shared turbine group to which the target wind turbine belongs from multiple shared turbine groups.
[0035] In this step, the server can associate and store each shared turbine cluster with the wind turbines it contains. For any wind turbine in the wind farm, the target shared turbine cluster to which the target wind turbine belongs can be determined based on this association.
[0036] S23, based on the current wind speed of each wind turbine in the target shared turbine cluster, determine the wind direction deviation of each wind turbine.
[0037] In this step, factors such as the geographical location of the wind turbine, operational errors during manual deployment, and north-alignment errors can cause wind direction deviations. To address this, we can analyze the wind direction deviations caused by these factors under different historical wind speeds, thereby determining the correlation between wind speed and wind direction deviation. Based on this correlation, we can predict the wind direction deviation of each wind turbine in the target shared turbine cluster at the current wind speed. The correlation between wind speed and wind direction deviation can be represented by a wind speed-wind direction deviation curve.
[0038] S24, based on the wind direction deviation of each wind turbine in the target shared turbine group, correct the wind direction of each wind turbine.
[0039] In this step, based on the wind direction deviation of each wind turbine in the target shared turbine cluster, the wind direction of each wind turbine is corrected to ensure that each wind turbine in the target shared turbine cluster has a relatively accurate wind direction.
[0040] S25, based on the corrected wind direction of each wind turbine in the target shared turbine cluster, determine the current wind direction of the target wind turbine.
[0041] In this step, since the wind direction of each wind turbine in the target shared wind turbine cluster has been corrected, the current wind direction of the target wind turbine can be determined more accurately based on the corrected wind direction of each wind turbine. For example, the average of the corrected wind directions of multiple wind turbines can be used to determine the current wind direction of the target wind turbine. Alternatively, different weighting coefficients can be set according to the distance between each wind turbine and the target wind turbine, with the weighting coefficient increasing for closer distances. The corrected wind directions of each wind turbine can be multiplied by their respective weighting coefficients and then summed to obtain the current wind direction of the target wind turbine.
[0042] S26, transmit the current wind direction and current wind speed of the target wind turbine to the target wind turbine so that the target wind turbine can adjust its operating status according to the current wind direction and current wind speed.
[0043] In this step, after the server determines the current wind direction of the target wind turbine, it can transmit both the current wind direction and current wind speed to the target wind turbine. This allows the target wind turbine to adjust its operating status based on the current wind direction and speed, primarily yaw and pitch. Since yaw and pitch adjustments are mainly performed with reference to wind direction, the current wind speed transmitted by the server to the target wind turbine can be the wind speed directly collected by meteorological instruments.
[0044] In the wind farm control method provided in this application embodiment, the server divides the wind turbines deployed within the wind farm into multiple shared turbine clusters. Within the same shared turbine cluster, the wind speeds and directions of the wind turbines are relatively similar. For any target wind turbine within the wind farm, the target shared turbine cluster to which the target wind turbine belongs can be determined. For each wind turbine in the target shared turbine cluster, the wind direction deviation of the wind turbine at the current wind speed can be determined, and the wind direction can be corrected based on the wind direction deviation. After the wind direction of each wind turbine in the target shared turbine cluster is corrected, the current wind direction of the target wind turbine can be determined based on the corrected wind direction of each wind turbine, and the current wind speed and current wind direction of the target wind turbine can be transmitted to the target wind turbine so that the target wind turbine can adjust its operating state according to the current wind speed and current wind direction.
[0045] In this embodiment, the current wind direction of the target wind turbine is determined based on the wind direction after correction for deviations from each wind turbine in the target shared turbine cluster. This means that wind direction deviations are considered when determining the current wind direction of the target wind turbine, resulting in a more accurate current wind direction. Due to the high consistency among wind turbines within the target shared turbine cluster, even if the wind speed and direction detected by the target wind turbine's own meteorological instruments are unreliable, the current wind direction of the target wind turbine can still be determined using the corrected wind directions from other wind turbines in the target shared turbine cluster, ensuring the reliability of the target wind turbine's current wind direction. Operating the wind turbine based on more accurate and reliable wind direction and speed reduces the likelihood of unbalanced loads on the wind turbine, thereby lowering the possibility of structural damage and improving the safety of the wind turbine.
[0046] The following describes the optional implementation methods of the wind farm control method provided in the embodiments of this application.
[0047] Optional, combined Figure 3 As shown, in step S21 above, the step of the server dividing the wind turbines in the wind farm to obtain multiple shared turbine clusters includes: S31, based on the historical wind condition data of each wind turbine in the wind farm, groups are formed to obtain multiple wind turbine groups.
[0048] In this step, to ensure the reliability of historical wind data (including historical wind direction and historical wind speed), the selected historical wind data should not be too early. For example, historical wind data from the most recent month can be selected. Historical wind data can be represented using a wind rose diagram, which visually reflects the prevailing wind direction and frequency. When grouping, wind turbines with similar prevailing wind directions and frequencies can be grouped together.
[0049] S32, filter out wind turbines that are affected by wake interference from multiple wind turbine groups.
[0050] In this step, considering that the wind condition data provided by wind turbines affected by wake interference is not very reliable, it is necessary to screen out wind turbines affected by wake interference from the wind turbine group. Specifically, based on the geographical location of each wind turbine, it is determined whether the wind turbine is downwind of other wind turbines. If the wind turbine is downwind of other wind turbines, it means that the wind turbine is very likely in the wake region of other wind turbines, which also means that the wind turbine is affected by wake interference.
[0051] S33, based on historical wind data of each wind turbine in the wind farm, determines the turbulence intensity of each wind turbine.
[0052] In this step, turbulence intensity is used to represent the degree of drastic change in wind direction and speed over time, reflecting the stability of wind conditions. The turbulence intensity of a wind turbine is related to the load it bears and the terrain it is located in. By determining the turbulence intensity of each wind turbine and grouping turbines with the same turbulence level into the same shared turbine location group, it is ensured that the loads borne by each wind turbine in the same shared turbine location group are similar, and the degree of wind stability is also similar.
[0053] S34. The wind turbines within a preset distance in each shared turbine group are divided into the same shared turbine group, resulting in multiple shared turbine groups.
[0054] In this step, considering that wind turbines located close to each other have similar environmental conditions and similar operating states, they are grouped into the same shared turbine cluster. The preset distance can be set according to requirements.
[0055] Using this implementation method, the wind turbines in the shared turbine cluster obtained under various consistency constraints maintain a high degree of consistency. Therefore, based on the operating status of each wind turbine in the shared turbine cluster, the wind conditions of each wind turbine can be analyzed more accurately, so as to carry out fine control of the wind turbines in the wind farm based on accurate wind conditions.
[0056] Furthermore, before grouping the historical wind condition data of each wind turbine in the wind farm, the server can perform preprocessing on the historical wind condition data of each wind turbine. This preprocessing includes at least time synchronization, outlier removal, and filtering.
[0057] In this implementation, for historical wind condition data with a time series, historical wind condition data from the same time period or the same moment are of reference value. Time synchronization processing ensures that historical wind direction and speed in the historical wind condition data are at the same time scale. Historical wind condition data may also contain anomalous data, such as data outside the range of meteorological instruments or abnormal fluctuations. Screening out anomalous data reduces invalid data in the historical wind condition data. Considering that historical wind condition data may also contain noisy data, filtering processing can eliminate noisy data in the historical wind condition data, thereby obtaining stable historical wind condition data.
[0058] By employing this implementation method, the quality of historical wind data can be improved by preprocessing the historical wind data of wind turbines, enabling the historical wind data to more accurately reflect the historical operating status of wind turbines.
[0059] Optionally, the server deploys a pre-trained bias calculation model, which can be an LSTM (Long Short-Term Memory) model. Combined with... Figure 4 As shown, the steps for training the bias calculation model include: S41: Obtain the historical wind speed of the wind turbine and divide the historical wind speed into multiple wind speed ranges.
[0060] In this step, the historical wind speed is divided into multiple wind speed intervals according to preset intervals. For example, dividing the historical wind speed from 0 to 25 m / s into preset intervals of 1 m / s, we can obtain wind speed interval 1 (0-1 m / s), wind speed interval 2 (1 m / s-2 m / s), wind speed interval 3 (2 m / s-3 m / s), ... wind speed interval 25 (24 m / s-25 m / s).
[0061] S42, determine the wind direction deviation for each wind speed range, and obtain the correlation between each wind speed range and the wind direction deviation.
[0062] In this step, based on historical wind data, the wind direction deviation of the wind turbine can be determined when the wind speed is in different wind speed zones, thus obtaining the correlation between each wind speed zone and the wind direction deviation. The correlation between each wind speed zone and the wind direction deviation can be represented by the wind speed zone-wind direction deviation curve, which can reflect the nonlinear relationship between different wind speed characteristics and wind direction deviation.
[0063] S43, train the initial model so that it learns the correlation between wind speed ranges and wind direction deviations, and obtain a trained deviation calculation model.
[0064] In this step, the initial model is used to learn the correlation between wind speed ranges and wind direction deviations. This allows the initial model to learn the wind direction deviations caused by factors such as the geographical location of the wind turbine, operational errors in manual deployment, and northward errors when the wind turbine is in different wind speed ranges. This enables the trained deviation calculation model to identify the wind speed of the wind turbine and thus determine the wind direction deviation.
[0065] Furthermore, in step 23 above, the server determines the directional deviation of each wind turbine based on the current wind speed of each wind turbine in the target shared turbine cluster. This includes inputting the current wind speed of each wind turbine in the target shared turbine cluster into a trained deviation calculation model, so that the deviation calculation model can identify the wind speed of each wind turbine and output the wind direction deviation of each wind turbine. In this way, the wind direction deviation of the wind turbine can be determined relatively conveniently using the trained deviation calculation model.
[0066] Optionally, in step S26 above, the server transmits the current wind direction and current wind speed of the target wind turbine to the target wind turbine, including: determining whether the communication of the target wind turbine is normal based on the heartbeat information sent by the target wind turbine; transmitting the current wind direction and current wind speed to the target wind turbine when the communication of the target wind turbine is normal; and sending a communication error message when the communication of the target wind turbine is abnormal.
[0067] In this implementation, when the server sends wind condition parameters to the target wind turbine, it can determine whether the communication between the server and the target wind turbine is normal. Specifically, it can determine this based on the heartbeat information sent by the target wind turbine. Under normal communication conditions, the target wind turbine will periodically send heartbeat information to the server. When the heartbeat information sent by the target wind turbine is delayed or lost, it indicates a communication abnormality, and the server sends a communication abnormality prompt message. For example, the communication abnormality prompt message can be displayed to maintenance personnel through the running interactive interface, sent to a client carried by the maintenance personnel, or sent to the host computer of the target wind turbine, so that the host computer can display the prompt message to the maintenance personnel. The purpose of the communication abnormality prompt message is to instruct maintenance personnel to check the communication connection between the server and the target wind turbine. When the server receives the periodically sent heartbeat information from the target wind turbine, it indicates that the communication with the target wind turbine is normal, and the server can then transmit wind condition parameters to the target wind turbine.
[0068] By adopting this implementation method, when sending wind condition parameters to the target wind turbine, the communication status between the wind turbine and the target wind turbine is verified. This ensures that the wind condition parameters are sent to the target wind turbine when the communication is normal, thus ensuring that the wind condition parameters are accurately sent to the target wind turbine.
[0069] The following describes the product embodiments provided in this application.
[0070] Combination Figure 5 As shown, this application embodiment provides a wind farm control device 500, which can be integrated into the server of the aforementioned embodiment. The control device 500 includes a wind farm division module 501, a target determination module 502, a deviation determination module 503, a wind direction correction module 504, a wind direction determination module 505, and a wind condition transmission module 506.
[0071] The wind farm partitioning module 501 is configured to partition the wind turbines within the wind farm to obtain multiple shared turbine clusters.
[0072] The target determination module 502 is configured to determine the target shared turbine group to which the target wind turbine belongs from multiple shared turbine groups; the target wind turbine is any wind turbine in the wind farm.
[0073] The deviation determination module 503 is configured to determine the wind direction deviation of each wind turbine based on the current wind speed of each wind turbine in the target shared turbine cluster.
[0074] The wind direction correction module 504 is configured to correct the wind direction of each wind turbine based on the wind direction deviation of each wind turbine in the target shared turbine cluster.
[0075] The wind direction determination module 505 is configured to determine the current wind direction of the target wind turbine based on the corrected wind direction of each wind turbine in the target shared turbine cluster.
[0076] The wind condition transmission module 506 is configured to transmit the current wind direction and current wind speed of the target wind turbine to the target wind turbine so that the target wind turbine can adjust its operating status according to the current wind direction and current wind speed.
[0077] Optionally, the wind farm division module 501, when dividing the wind turbines within the wind farm, specifically performs the following: Grouping wind turbines based on historical wind condition data for each turbine within the wind farm, resulting in multiple wind turbine groups. Removing wind turbines affected by wake interference from the multiple wind turbine groups. Determining the turbulence intensity of each wind turbine based on historical wind condition data. Based on the turbulence intensity of each wind turbine in the wind farm, assigning wind turbines with the same turbulence level within each wind turbine group to the same shared turbine location group, resulting in multiple shared turbine location groups. Assigning wind turbines within each shared turbine location group that are within a preset distance to the same shared turbine location cluster, resulting in multiple shared turbine location clusters.
[0078] Optionally, before grouping the wind farms based on the historical wind condition data of each wind turbine within the wind farm, the wind farm division module 501 is also used to: perform preprocessing on the historical wind condition data of each wind turbine. This preprocessing includes at least time synchronization, outlier removal, and filtering.
[0079] Optionally, when the deviation determination module 503 determines the wind direction deviation of each wind turbine based on the current wind speed of each wind turbine in the target shared turbine group, it is specifically used to: input the current wind speed of each wind turbine into the deviation calculation model so that the deviation calculation model can identify the current wind speed of the wind turbine and output the wind direction deviation of the wind turbine.
[0080] Optionally, the control device 500 also includes a model training module 507, configured to acquire historical wind speeds of the wind turbine. The historical wind speeds are divided into multiple wind speed intervals. The wind direction deviation for each wind speed interval is determined, establishing the correlation between the wind speed intervals and the wind direction deviation. The initial model is trained to learn the correlation between the wind speed intervals and the wind direction deviation, resulting in a trained deviation calculation model.
[0081] Optionally, the wind condition transmission module 501 is specifically used to: determine whether the communication of the target wind turbine is normal based on the heartbeat information sent by the target wind turbine; when the communication of the target wind turbine is normal, transmit the current wind direction and current wind speed to the target wind turbine; when the communication of the target wind turbine is abnormal, send a communication abnormality prompt message.
[0082] The wind farm control device 500 provided in this application embodiment is used to implement the wind farm control method in the foregoing embodiment. The specific implementation method and beneficial effects can be referred to the foregoing embodiment, and will not be repeated here.
[0083] Combination Figure 6As shown, this application embodiment provides an electronic device 600, including a processor 601 and a memory 602. Optionally, the electronic device 600 may further include a communication interface 603 and a bus 604. The processor 601, memory 602, and communication interface 603 can communicate with each other via the bus 604. The communication interface 603 can be used for information transmission. The processor 601 can call logical instructions in the memory 602 to execute the wind farm control method described in the above embodiment.
[0084] Furthermore, the logic instructions in the aforementioned memory 602 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.
[0085] The memory 602, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 601 executes functional applications and data processing by running the program instructions / modules stored in the memory 602, thereby implementing the wind farm control method in the above embodiments.
[0086] The memory 602 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 602 may include high-speed random access memory and may also include non-volatile memory.
[0087] This application provides a storage medium storing computer-executable instructions, which are configured to execute the wind farm control method described in the above embodiments.
[0088] The aforementioned storage medium can be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.
[0089] The technical solutions of this application embodiment can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this application embodiment. The aforementioned storage medium can be a non-transitory storage medium, including: USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, and other media capable of storing program code; it can also be a transient storage medium.
[0090] This application provides a computer program product, including a computer program, which, when executed by a processor, implements the wind farm control method described in the above embodiments.
[0091] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.
[0092] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0093] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
Claims
1. A control method of a wind farm, characterized in that, The method applied to a server comprises: dividing wind turbines in the wind farm to obtain a plurality of shared machine position groups; determining a target shared machine position group to which a target wind turbine belongs from the plurality of shared machine position groups; the target wind turbine is any wind turbine in the wind farm; determining a wind direction deviation of each wind turbine based on a current wind speed of each wind turbine in the target shared machine position group; correcting a wind direction of each wind turbine in the target shared machine position group according to the wind direction deviation of each wind turbine; determining a current wind direction of the target wind turbine based on the corrected wind direction of each wind turbine in the target shared machine position group; transmitting the current wind direction and the current wind speed of the target wind turbine to the target wind turbine, so that the target wind turbine adjusts an operating state according to the current wind direction and the current wind speed.
2. The method of claim 1, wherein, The method for dividing wind turbines in the wind farm to obtain a plurality of shared machine position groups comprises: grouping wind turbines in the wind farm based on historical wind condition data of the wind turbines to obtain a plurality of wind turbine groups; screening out wind turbines disturbed by wake interference from the plurality of wind turbine groups; determining a turbulence intensity of each wind turbine in the wind farm based on historical wind condition data of the wind turbines; dividing wind turbines with the same turbulence level in each wind turbine group into the same shared machine position group according to the turbulence intensity of each wind turbine in the wind farm to obtain a plurality of shared machine position groups; dividing wind turbines within a preset distance in each shared machine position group into the same shared machine position group to obtain a plurality of shared machine position groups.
3. The method of claim 2, wherein, Before grouping the wind turbines in the wind farm based on the historical wind condition data of the wind turbines, the method further comprises: performing preprocessing on the historical wind condition data of the wind turbines; wherein the preprocessing at least includes time processing, abnormal data processing and filtering processing.
4. The method of claim 1, wherein, The method for determining a wind direction deviation of each wind turbine based on a current wind speed of each wind turbine in the target shared machine position group comprises: for each wind turbine in the target shared machine position group, inputting the current wind speed of the wind turbine into a deviation calculation model, so that the deviation calculation model identifies the current wind speed of the wind turbine and outputs a wind direction deviation of the wind turbine.
5. The method of claim 4, wherein, Before inputting the wind speed of the wind turbine into the deviation calculation model, the method further comprises: obtaining a historical wind speed of the wind turbine; dividing the historical wind speed to obtain a plurality of wind speed intervals; determining a wind direction deviation of each wind speed interval to obtain a correlation between the wind speed interval and the wind direction deviation; training an initial model to learn the correlation between the wind speed interval and the wind direction deviation to obtain a trained deviation calculation model.
6. The method of claim 1, wherein, The method for transmitting the current wind direction and the current wind speed of the target wind turbine to the target wind turbine comprises: judging whether the communication of the target wind turbine is normal according to heartbeat information sent by the target wind turbine; when the communication of the target wind turbine is normal, transmitting the current wind direction and the current wind speed to the target wind turbine.
7. The method of claim 6, wherein, The method further comprises: sending prompt information of communication abnormality when the communication of the target wind turbine is abnormal.
8. A control device of a wind farm, characterized by comprising: The device is integrated in a server, and the device comprises: a wind farm division module configured to divide wind turbines in the wind farm to obtain a plurality of shared site groups; a target determination module configured to determine a target shared site group to which a target wind turbine belongs from the plurality of shared site groups; the target wind turbine is any wind turbine in the wind farm; a deviation determination module configured to determine a wind direction deviation of each wind turbine in the target shared site group based on a current wind speed of each wind turbine in the target shared site group; a wind direction correction module configured to correct a wind direction of each wind turbine in the target shared site group according to the wind direction deviation of each wind turbine in the target shared site group; a wind direction determination module configured to determine a current wind direction of the target wind turbine based on the corrected wind direction of each wind turbine in the target shared site group; a wind condition transmission module configured to transmit the current wind direction and the current wind speed of the target wind turbine to the target wind turbine, so that the target wind turbine adjusts an operation state according to the current wind direction and the current wind speed.
9. An electronic device comprising a processor and a memory having stored program instructions, wherein the program instructions, when executed by the processor, cause the electronic device to perform the method of any one of claims 1-8. The processor is configured to execute the wind farm control method of any one of claims 1 to 7 when the program instructions are executed.
10. A storage medium storing program instructions, characterized in that, The program instructions are executed to perform the wind farm control method of any one of claims 1 to 7.